107 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Flavors of biotin ligases: From research tools towards biopharmaceutical applications

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    Biotin ligases are enzymes commonly attaching biotin to biotin-dependent enzymes, which are fundamental for essential metabolic pathways like gluconeogenesis or fatty acids synthesis. However, in times of protein engineering and genome editing those enzymes can be utilized in versatile ways. In this work biotin ligases were deployed in different fields of research starting with a tool for fundamental understanding of cell biology and culminating in biopharmaceutical approaches. First, a novel enzyme called ultraID applicable for protein-protein interaction studies was engineered by directed evolution. This undertaking was carried out by error-prone PCR mutagenesis and yeast surface display in combination with fluorescence activated cell sorting. While based on a biotin ligase derived from Aquifex aeolicus the novel enzyme exhibited a massively improved catalytic turnover, which was tracked back to one single mutation in the active site. To date, ultraID is one of the smallest and most efficient enzymes for the proximity-dependent biotin identification method. Second, screening of the randomized biotin ligase library was conducted towards a modified biotin substrate. Hereby, a propargyl functionalized biotin derivative was examined for enzyme turnover. Even tough different yeast surface presentation and assay strategies were analyzed a propargyl biotin using enzymes was not identified. Third, fundamental experiments for the generation of an antibody-drug conjugate by biotin ligases were performed. A biotin ligase derived from Pyrococcus horikoshii was exploited to conjugate propargyl biotin and desthiobiotin azide to the therapeutic antibody trastuzumab, which was equipped with a biotin acceptor domain. It was successfully demonstrated that chemoenzymatic modification was feasible by conjugating a fluorophore to the antibody. However, the usage of desthiobiotin azide as a substrate renders the biotin ligase unspecific and consequently, optimizations must be done in future approaches. In parallel an antibody-drug conjugate was generated by a different approach. Lipoate-protein ligase A derived from Escherichia coli was used to conjugate a click chemistry moiety to a tagged trastuzumab. Subsequent attachment of a Monomethyl auristatin E toxin led to the generation of an antibody-drug conjugate with potency in the picomolar range. Additionally, it was shown that the applied conjugation strategy had no impact on the antibodies affinity and enzymatic conjugation was complete within a few minutes. Last, identification of internalizing single-chain variable fragments out of systemic lupus erythematosus phage display library was executed. Hereby different enrichment strategies were examined involving incubation on mammalian cells and biotinylation of phages upon successful cell penetration. Ultimately, discovery of an internalizing binder was not achieved but crucial knowledge on phage display-based enrichment of cell penetrating binders was obtained

    Lessons from Formally Verified Deployed Software Systems (Extended version)

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    The technology of formal software verification has made spectacular advances, but how much does it actually benefit the development of practical software? Considerable disagreement remains about the practicality of building systems with mechanically-checked proofs of correctness. Is this prospect confined to a few expensive, life-critical projects, or can the idea be applied to a wide segment of the software industry? To help answer this question, the present survey examines a range of projects, in various application areas, that have produced formally verified systems and deployed them for actual use. It considers the technologies used, the form of verification applied, the results obtained, and the lessons that can be drawn for the software industry at large and its ability to benefit from formal verification techniques and tools. Note: a short version of this paper is also available, covering in detail only a subset of the considered systems. The present version is intended for full reference.Comment: arXiv admin note: text overlap with arXiv:1211.6186 by other author

    GPU-based Architecture Modeling and Instruction Set Extension for Signal Processing Applications

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    The modeling of embedded systems attempts to estimate the performance and costs prior to the implementation. The early stage predictions for performance and power dissipation reduces the more costly late stage design modifications. Workload modeling is an approach where an abstract application is evaluated against an abstract architecture. The challenge in modeling is the balance between fidelity and simplicity, where fidelity refers to the correctness of the predictions and the simplicity relates to the simulation time of the model and its ease of comprehension for the developer. A model named GSLA for performance and power modeling is presented, which extends existing architecture modeling by including GPUs as parallel processing elements. The performance model showed an average fidelity of 93% and the power model demonstrated an average fidelity of 84% between the models and several application measurements. The GSLA model is very simple: only 2 parameters that can be obtained by automated scripts. Besides the modeling, this thesis addresses lower level signal processing system improvements by proposing Instruction Set Architecture (ISA) extensions for RISC-V processors. A vehicle classifier neural network model was used as a case study, in which the benefit of Bit Manipulation Instructions (BMI) is shown. The result is a new PopCount instruction extension that is verified in ETISS simulator. The PopCount extension of RISC-V ISA showed a performance improvement of more than double for the vehicle classifier application. In addition, the design flow for adding a new instruction extension for a re-configurable platform is presented. The GPU modeling and the RISC-V ISA extension added new features to the state of the art. They improve the modeling features as well as reduce the execution costs in signal processing platforms

    Proceedings of the 22nd Conference on Formal Methods in Computer-Aided Design – FMCAD 2022

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    The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

    Shader optimization and specialization

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    In the field of real-time graphics for computer games, performance has a significant effect on the player’s enjoyment and immersion. Graphics processing units (GPUs) are hardware accelerators that run small parallelized shader programs to speed up computationally expensive rendering calculations. This thesis examines optimizing shader programs and explores ways in which data patterns on both the CPU and GPU can be analyzed to automatically speed up rendering in games. Initially, the effect of traditional compiler optimizations on shader source-code was explored. Techniques such as loop unrolling or arithmetic reassociation provided speed-ups on several devices, but different GPU hardware responded differently to each set of optimizations. Analyzing execution traces from numerous popular PC games revealed that much of the data passed from CPU-based API calls to GPU-based shaders is either unused, or remains constant. A system was developed to capture this constant data and fold it into the shaders’ source-code. Re-running the game’s rendering code using these specialized shader variants resulted in performance improvements in several commercial games without impacting their visual quality

    Simulation methodologies for mobile GPUs

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    GPUs critically rely on a complex system software stack comprising kernel- and user-space drivers and JIT compilers. Yet, existing GPU simulators typically abstract away details of the software stack and GPU instruction set. Partly, this is because GPU vendors rarely release sufficient information about their latest GPU products. However, this is also due to the lack of an integrated CPU-GPU simulation framework, which is complete and powerful enough to drive the complex GPU software environment. This has led to a situation where research on GPU architectures and compilers is largely based on outdated or greatly simplified architectures and software stacks, undermining the validity of the generated results. Making the situation even more dire, existing GPU simulation efforts are concentrated around desktop GPUs, making infrastructure for modelling mobile GPUs virtually non-existent, despite their surging importance in the GPU market. Still, mobile GPU designers are faced with the challenge of evaluating design alternatives involving hundreds of architectural configuration options and micro-architectural improvements under tight time-to-market constraints, to which currently employed design flows involving detailed, but slow simulations are not well suited. In this thesis we develop a full-system simulation environment for a mobile platform, which enables users to run a complete and unmodified software stack for a state-of-the-art mobile Arm CPU and Mali Bifrost GPU powered device, achieving 100\% architectural accuracy across all available toolchains. We demonstrate the capability of our GPU simulation framework through a number of case studies exploring modern, mobile GPU applications, and optimize them using functional simulation statistics, unavailable with other approaches or hardware. Furthermore, we develop a trace-based performance model, allowing architects to rapidly model GPU configurations in early design space exploration

    Computer Aided Verification

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    This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

    Smart Wireless Sensor Networks

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    The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks
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